In addition, under rarely contended workloads such as TPC-C, PARE matches the performance of transaction pipeline due to its low runtime overhead.
We first compared PIGGY with other methods for the TPS case, which reflected the performance of transaction processing while executing various workloads.
This also shows that the performance of transaction pipeline is not sensitive to single highly contended operation and two consecutive highly contended operations, which supports our defined "harmful ordering" because one contended operation and two consecutive contended operations do not form harmful ordering.
Finally, we report a rather devastating result with regard to the overall performance of RMBS transactions.
Nested transactions allow increased parallel execution of transactions, and handle transaction aborts in our system.
In another example, a TPC-C test measures the performance of a transaction, so the target subject is "performance".
To enhance performance of data transaction, the approach retains heavy-mass data necessary for routine query within the database server, (e.g., clinical variables, PROs and PCRs) and accesses lightweight data for online analysis in the Web server, (e.g., decision support criteria, treatment guidelines).
We have measured performances of posted transactions (Swrite and Nwrite) and non-posted transactions (Nread and Nwrite_R) by sending several packets from one C6678 DSP to another through the CPS1848 SRIO switch using the SRDP2.
The experimental results show that our framework improves the performance of e-commerce transactions while providing a high quality of security services for desired e-commerce transactions.
Second, the proposed framework is based on a dynamic mapping mechanism that improves the performance of e-commerce transactions.
